Related references
Note: Only part of the references are listed.Multi-channel Raman Spectral Reconstruction Based on Gaussian Kernel Principal Component Analysis
Wang Xin et al.
ACTA PHOTONICA SINICA (2020)
Cancer incidence and mortality in China, 2014
Wanqing Chen et al.
CHINESE JOURNAL OF CANCER RESEARCH (2018)
Iterative random forests to discover predictive and stable high-order interactions
Sumanta Basu et al.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2018)
Cancer Characteristic Gene Selection via Sample Learning Based on Deep Sparse Filtering
Jian Liu et al.
SCIENTIFIC REPORTS (2018)
Supervised Penalty Matrix Decomposition for Tumor Differentially Expressed Genes Selection
Liu Jian et al.
CHINESE JOURNAL OF ELECTRONICS (2018)
A balanced iterative random forest for gene selection from microarray data
Ali Anaissi et al.
BMC BIOINFORMATICS (2013)
Improving accuracy of microarray classification by a simple multi-task feature selection filter
Liang Lan et al.
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS (2011)
Accelerating the kernel-method-based feature extraction procedure from the viewpoint of numerical approximation
Yong Xu et al.
NEURAL COMPUTING & APPLICATIONS (2011)
Producing computationally efficient KPCA-based feature extraction for classification problems
Y. Xu et al.
ELECTRONICS LETTERS (2010)
Simultaneous genes and training samples selection by modified particle swarm optimization for gene expression data classification
Qi Shen et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2009)
An efficient semi-unsupervised gene selection method via spectral biclustering
Bing Liu et al.
IEEE TRANSACTIONS ON NANOBIOSCIENCE (2006)
A simple generalisation of the area under the ROC curve for multiple class classification problems
DJ Hand et al.
MACHINE LEARNING (2001)